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lktslionel/main.py

Created July 25, 2024 08:18
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Railway Programming with Python Returns library
Raw
main.py
import random
from functools import partial
from typing import Any, Dict, List, Optional
from returns.pipeline import flow
from returns.pointfree import alt, bind, lash, map
from returns.result import Failure, Result, Success
from dataclasses import dataclass
Metadata = Dict[str, Any]
@dataclass(kw_only=True)
class NoEntriesFoundError(Exception):
count: int
def __init__(self, count: int) -> None:
self.count = count
super().__init__("No entries found")
@dataclass(kw_only=True)
class NoAttributeIdFoundError(Exception):
attrs: Optional[Dict] = None
def __init__(self, *, attrs=None) -> None:
self.attrs = attrs
super().__init__("No attribute 'id' found")
@dataclass(kw_only=True)
class MetadataEntryNotFound(Exception):
attrs: Optional[Dict] = None
id: Optional[str] = None
def __init__(
self,
*,
id: Optional[str] = None,
attrs=None,
) -> None:
self.id = id
self.attrs = attrs
super().__init__(f"No metadata entry found with id[{id}]")
Error = NoEntriesFoundError | NoAttributeIdFoundError | MetadataEntryNotFound
def find_metadata_entries(
count: int) -> Result[List[Metadata], NoEntriesFoundError]:
#print(f"count: {count}")
if count == 0:
return Failure(NoEntriesFoundError(count))
metas = [{"id": str(x)} for x in range(count)]
#print(f"metas: {metas}")
return Success(metas)
def filter_metadata_by_id(
metas: List[Metadata],
attrs: Optional[Dict] = None
) -> Result[Metadata, NoAttributeIdFoundError | MetadataEntryNotFound]:
#print(f"filter_metadata_by_id.attrs: {attrs}")
#print(f"filter_metadata_by_id.metas: {metas}")
id = attrs.get("id") if attrs else None
if id is None:
return Failure(NoAttributeIdFoundError(attrs=attrs))
meta = next(filter(lambda x: x.get("id") == id, metas), None)
if not meta:
return Failure(MetadataEntryNotFound(id=id, attrs=attrs))
return Success(meta)
def fallback_with_a_single_entry(
err: NoEntriesFoundError) -> Result[Any, Error]:
match err:
case NoEntriesFoundError():
print("[FALLBACK]: ValueError: {}".format(err))
print("[FALLBACK]: Trying with one entry")
return find_metadata_entries(1)
case _:
print("[DEBUG]: Exception: {}".format(err))
return Failure(err)
def debug_on_failure(err: Failure) -> Result[Any, Exception]:
match err:
case ValueError():
print("[DEBUG]: err: {}".format(err))
case Exception():
print("[DEBUG]: Exception: {}".format(err))
return err
def find_by_attrs(
count: int,
*,
attrs: Optional[Dict[str, Any]] = None) -> Result[Metadata, Exception]:
if attrs is None:
attrs = {}
return flow(
count,
find_metadata_entries,
lash(fallback_with_a_single_entry),
alt(debug_on_failure),
bind(partial(filter_metadata_by_id, attrs=attrs)),
)
if __name__ == '__main__':
# import pdb
# pdb.set_trace()
# breakpoint()
calls = [
# find_by_attrs(5, attrs={"id": "2"}),
find_by_attrs(0),
# find_by_attrs(
# 1,
# attrs={"no": False},
# ),
# find_by_attrs(
# 2,
# attrs={"id": "3"},
# ),
]
match random.choice(calls):
case Failure(err):
print(f"Failure: Error: {err}")
case Success(meta):
print(f"Success: Meta: {meta}")
Raw
requirements.txt
asttokens==2.4.1 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24 \
--hash=sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0
colorama==0.4.6 ; python_version >= "3.10" and python_version < "3.12" and sys_platform == "win32" \
--hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
--hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
decorator==5.1.1 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330 \
--hash=sha256:b8c3f85900b9dc423225913c5aace94729fe1fa9763b38939a95226f02d37186
exceptiongroup==1.2.2 ; python_version >= "3.10" and python_version < "3.11" \
--hash=sha256:3111b9d131c238bec2f8f516e123e14ba243563fb135d3fe885990585aa7795b \
--hash=sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc
executing==2.0.1 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:35afe2ce3affba8ee97f2d69927fa823b08b472b7b994e36a52a964b93d16147 \
--hash=sha256:eac49ca94516ccc753f9fb5ce82603156e590b27525a8bc32cce8ae302eb61bc
ipython==8.26.0 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:1cec0fbba8404af13facebe83d04436a7434c7400e59f47acf467c64abd0956c \
--hash=sha256:e6b347c27bdf9c32ee9d31ae85defc525755a1869f14057e900675b9e8d6e6ff
jedi==0.19.1 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd \
--hash=sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0
matplotlib-inline==0.1.7 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90 \
--hash=sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca
parso==0.8.4 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:a418670a20291dacd2dddc80c377c5c3791378ee1e8d12bffc35420643d43f18 \
--hash=sha256:eb3a7b58240fb99099a345571deecc0f9540ea5f4dd2fe14c2a99d6b281ab92d
pexpect==4.9.0 ; python_version >= "3.10" and python_version < "3.12" and (sys_platform != "win32" and sys_platform != "emscripten") \
--hash=sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 \
--hash=sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f
prompt-toolkit==3.0.47 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:0d7bfa67001d5e39d02c224b663abc33687405033a8c422d0d675a5a13361d10 \
--hash=sha256:1e1b29cb58080b1e69f207c893a1a7bf16d127a5c30c9d17a25a5d77792e5360
ptyprocess==0.7.0 ; python_version >= "3.10" and python_version < "3.12" and (sys_platform != "win32" and sys_platform != "emscripten") \
--hash=sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35 \
--hash=sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220
pure-eval==0.2.3 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0 \
--hash=sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42
pygments==2.18.0 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:786ff802f32e91311bff3889f6e9a86e81505fe99f2735bb6d60ae0c5004f199 \
--hash=sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a
returns==0.23.0 ; python_full_version >= "3.10.0" and python_version < "3.12" \
--hash=sha256:27594c28e5fc338e052d27ddf77fe1da82db4472f6d59901e7e9165be35a5256 \
--hash=sha256:278aa6168072b24574ad14be32f7123d1b835928473dd40bc506f47c8b25859a
six==1.16.0 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926 \
--hash=sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254
stack-data==0.6.3 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9 \
--hash=sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695
traitlets==5.14.3 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7 \
--hash=sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f
typing-extensions==4.12.2 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \
--hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8
wcwidth==0.2.13 ; python_version >= "3.10" and python_version < "3.12" \
--hash=sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859 \
--hash=sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5
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